WelchConsultingEmploymentIndexShowsGainsinJanuary

Posted by Super User

on 07 February 2018

The Welch Consulting Employment Index increased from 100.9 to 101.0 in January. The index continues to be near its highest level since July, 2008. The index for men reached 99.2, the highest it has been since September, 2008.

The Welch Index measures full-time equivalent employment after adjustment for population growth and the aging of the workforce. An Index value of 100.0 indicates that adjusted full-time equivalent employment is the same as its level in the base year of 2004.

Over the past 12 months the index has risen from 100.0 to 101.0. The increase in the Index over the past year means that full-time equivalent employment has been growing at a faster rate than the adult population. Full-time equivalent employment increased 1.0% faster than the adult population over the past year (after making adjustments for the aging of the U.S. adult population). Looking back at the most recent 6 months, the index increased from 100.6 in July to 101.0 currently – an increase of 0.45%. The rate of change over the past year and the past six months is on pace with the overall trend for the last 3 years of about 1.0% increase per year.

The indices for men and women continued moving in opposite directions this month. The index for women had a small decline for the third month in a row, falling 0.2 points from 103.3 to 103.1. The index for men rose 0.3 points this month, from 98.9 to 99.2. For the past 12 months the index for men has risen 0.6 points and the index for women has risen 1.3 points.

Technical Note: Full-time equivalent employment equals full-time employment plus one half of part-time employment from the BLS household survey (the Current Population Survey). The data reported for a given month is generally from the calendar week that contains the 12th day of the month. The Welch index adjusts for the changing age distribution of the population by fixing the age distribution of adults to the distribution in the base year of 2004. Seasonal effects for the share of workers employed in part-time jobs are removed in a regression framework using monthly indicator variables.